ENSINO DO PENSAMENTO COMPUTACIONAL NA EDUCAÇÃO BÁSICA

A cognição é um processo de aquisição do conhecimento que se baseia em experiências sensoriais, pensamentos, representações e recordações [1]. O desenvolvimento cognitivo está relacionado ao aprimoramento das habilidades de raciocinar, tomar decisões, memorizar e perceber o ambiente, que por sua vez se relacionam as práticas fundamentais da programação de computadores. Visto que a Sociedade Brasileira de Computação (SBC) defende que é fundamental o ensino da lógica de programação na educação básica, viu-se a possibilidade de estimular esse desenvolvimento com práticas de programação de jogos. Este trabalho apresenta a plataforma desenvolvida, assim como a experiência adquirida até o momento. De forma geral, pode-se notar que o jogo permitiu a evolução cognitiva da maioria das crianças, o pensamento computacional, assim como possibilitou a inclusão digital das mesmas.

Absence of Fas-L aggravates renal injury in acute Trypanosoma cruzi infection

Trypanosoma cruzi infection induces diverse alterations in immunocompetent cells and organs, myocarditis and congestive heart failure. However, the physiological network of disturbances imposed by the infection has not been addressed thoroughly. Regarding myocarditis induced by the infection, we observed in our previous work that Fas-L-/- mice (gld/gld) have very mild inflammatory infiltration when compared to BALB/c mice. However, all mice from both lineages die in the early acute phase. Therefore, in this work we studied the physiological connection relating arterial pressure, renal function/damage and cardiac insufficiency as causes of death. Our results show that a broader set of dysfunctions that could be classified as a cardio/anaemic/renal syndrome is more likely responsible for cardiac failure and death in both lineages. However, gld/gld mice had very early glomerular deposition of IgM and a more intense renal inflammatory response with reduced renal filtration, which is probably responsible for the premature death in the absence of significant myocarditis in gld/gld.Instituto Oswaldo Cruz-Fiocruz Laboratório de Biologia CelularUniversidade Federal do Rio de Janeiro Instituto de Biofísica Carlos Chagas FilhoUniversidade Federal Fluminense Instituto Biomédico Departamento de Fisiologia e FarmacologiaUniversidade Federal de São Paulo (UNIFESP) Escola Paulista de Medicina Disciplina de NefrologiaCentro de Criação de Animais de Laboratório Departamento de Controle de Qualidade AnimalUNIFESP, EPM, Disciplina de NefrologiaSciEL

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Catálogo Taxonômico da Fauna do Brasil: setting the baseline knowledge on the animal diversity in Brazil

The limited temporal completeness and taxonomic accuracy of species lists, made available in a traditional manner in scientific publications, has always represented a problem. These lists are invariably limited to a few taxonomic groups and do not represent up-to-date knowledge of all species and classifications. In this context, the Brazilian megadiverse fauna is no exception, and the Catálogo Taxonômico da Fauna do Brasil (CTFB) (http://fauna.jbrj.gov.br/), made public in 2015, represents a database on biodiversity anchored on a list of valid and expertly recognized scientific names of animals in Brazil. The CTFB is updated in near real time by a team of more than 800 specialists. By January 1, 2024, the CTFB compiled 133,691 nominal species, with 125,138 that were considered valid. Most of the valid species were arthropods (82.3%, with more than 102,000 species) and chordates (7.69%, with over 11,000 species). These taxa were followed by a cluster composed of Mollusca (3,567 species), Platyhelminthes (2,292 species), Annelida (1,833 species), and Nematoda (1,447 species). All remaining groups had less than 1,000 species reported in Brazil, with Cnidaria (831 species), Porifera (628 species), Rotifera (606 species), and Bryozoa (520 species) representing those with more than 500 species. Analysis of the CTFB database can facilitate and direct efforts towards the discovery of new species in Brazil, but it is also fundamental in providing the best available list of valid nominal species to users, including those in science, health, conservation efforts, and any initiative involving animals. The importance of the CTFB is evidenced by the elevated number of citations in the scientific literature in diverse areas of biology, law, anthropology, education, forensic science, and veterinary science, among others

Impact of COVID-19 on cardiovascular testing in the United States versus the rest of the world

Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-US institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection

Biodiesel and Bioplastic Production from Waste-Cooking-Oil Transesterification: An Environmentally Friendly Approach

Alternative sources of fuel have been a concern in the last few decades. The growth of urbanization and industrialization will lead to the exhaustion of fossil fuels, attracting studies on alternative routes. The main aim of this study was to produce biodiesel from waste cooking oil (WCO) by methyl transesterification using sodium hydroxide as a catalyst. For this, the physicochemical parameters of biodiesel were studied in triplicate (density, acidity, saponification, viscosity, corrosiveness to copper, visual appearance, and cloud point). An analysis by thin layer chromatography and infrared spectrometry was also performed. The increase in yield (83.3%) was directly proportional to the increase in the catalyst (0.22 g of NaOH). The infrared absorption spectra of WCO and biodiesel showed the presence of common and singular bands of each material. Furthermore, a simple and low-cost mechanism was proposed for purifying glycerol. The spectra of glycerol versus purified glycerin showed that the glycerin produced was pure, being used in the formulation of bioplastic. The product was checked for biodegradation and photodegradation, with incredible soil-degradation times of 180 days and photodegradation of only 60 days. In this way, biodiesel production from WCO showed environmentally friendly proposals and applicability. As the next steps, it is necessary to test the biodiesel produced in combustion engines and improve the bioplastic production, including a spectroscopic characterization and extensive biodegradation testing